Data Mining - Problem

About

A page about the problem definition in data

Characteristic

• Type of target: nominal or quantitative
  • Type of target class: binomial of multiclass
• Number of parameters: Data Mining - Dimensionality (number of variable, parameter) (P)
• Type of (predictor|features): nominal or numeric.
  • Mixed feature vectors (qualitative and quantitative)
• Model Complexity (Linear, Quadratic, …)
• Large data set or Not. Big N
• N bigger or smaller than P
• Is the target consistent or random ?
• Environment: noisy or not.

Type of problem

• classification, which attempts to assign each input value to one of a given set of classes (for example, determine whether a given email is “spam” or “non-spam”).
• regression, which assigns a real-valued output to each input;
• sequence labeling, which assigns a class to each member of a sequence of values (for example, part of speech tagging, which assigns a part of speech to each word in an input sentence);
• parsing, which assigns a parse tree to an input sentence, describing the syntactic structure of the sentence.